We are now at a major cross-roads in HIV drug redevelopment. Should we be satisfied with the current state of protease inhibitor (PI) drug development -- accepting that drug resistance and class cross-resistance are common -- and instead focus our efforts on the development of compounds that target other molecules (e.g. gp41 and integrase) or should we attempt to use the large amount of data that has been accumulated about PI resistance to also develop new inhibitors active against a broader range of drug-susceptible and drug-resistant virus isolates? The current generation of PIs have been developed using rational drug design techniques and drug screening targeted against wildtype subtype B viruses. Although lip service has been paid to need to consider inter-subtype variability and known drug-resistant variants in designing new PIs, there has been no concerted effort to categorize and use this information to PI drug design. Our group has created an online database, HIV RT & Protease Sequence Database (HIVRT&PrDB, http://hivdb.stanford.edu) to correlate reverse transcriptase (RT) and protease sequences with clinical and in vitro drug susceptibility data. The goal of this program project proposal is to expand, analyze and restructure the HIVRT&PrDB to provide information useful to the design of new inhibitory compounds against a range of drug-susceptible and drugresistant protease variants. We will use a combination of statistical and data mining approaches to identify clinically significant protease mutability constraints and to suggest biophysical and modeling experiments for the other program project participants. This work is particularly suited to a multidisciplinary academic collaboration that brings together investigators with strong track records in understanding the genetic, structural, and virologic mechanisms of HIV-1 protease resistance (Drs. Shafer, Schiffer, Swanstrom), two leading structural computational biologists with complementary expertises (Dr. Gilson, Tidor), and a core facility for the combinatorial synthesis and screening of test inhibitors (Dr. Rana). If successful, this research will not only lead to improvements in HIV drug treatment, but will also demonstrate that large amounts of correlated sequence data provide insight into the fine structure of a protein, its ligand binding, and its inhibition.